阮晓钢, 赵建伟. 基于Hopfield网络的柔性两轮自平衡机器人控制[J]. 机器人, 2010, 32(3): 405-413.
引用本文: 阮晓钢, 赵建伟. 基于Hopfield网络的柔性两轮自平衡机器人控制[J]. 机器人, 2010, 32(3): 405-413.
RUAN Xiaogang, ZHAO Jianwei. Flexible Two-wheeled Self-balancing Robot Control Based on Hopfield Neural Network[J]. ROBOT, 2010, 32(3): 405-413.
Citation: RUAN Xiaogang, ZHAO Jianwei. Flexible Two-wheeled Self-balancing Robot Control Based on Hopfield Neural Network[J]. ROBOT, 2010, 32(3): 405-413.

基于Hopfield网络的柔性两轮自平衡机器人控制

Flexible Two-wheeled Self-balancing Robot Control Based on Hopfield Neural Network

  • 摘要: 用弹簧模仿人的腰椎,采用LQR成功实现了机器人实物控制.针对柔性两轮自平衡机器人的姿态控制,提出了一种基于联想学习的离散Hopfield网络实现方法,以生物学习控制方式实现柔性两轮自平衡机器人在姿态控制上的自适应、自组织能力.针对非线性、强耦合的柔性机器人系统,首先定义了合理的能量变化函数,并运用柔性机器人动力学方程设计了满足该动态过程的Hopfield网络控制器,然后分析了该控制器的收敛性.仿真实验表明了该方法的有效性和系统的稳定性.对实验结果进行详细分析,表明了系统姿态控制器设计的合理性和有效性.

     

    Abstract: Real control of robot is realized successfully by using spring to imitate the lumbar of human-being and adopt-ing LQR(linear quadratic regulator).For posture control of the flexible two-wheeled self-balancing robot,a kind of discrete Hopfield network way based on associative study is presented,and self-adaptive and self-organizing posture control is accom-plished in a manner of biological control.Firstly,a reasonable energy function is defined for the nonlinear,strong coupling and flexible robot system.Then,a Hopfield neural network controller suitable for this dynamic process is designed based on the dynamics equation of the flexible robot,and its convergence is analyzed.Simulation experiments show the effectiveness of the method and prove the stability of the system.The rationality and availability of the system posture controller design are indicated through analyzing the experiment results in detail.

     

/

返回文章
返回